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apache/incubator-kvrocks

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4,339 نجوم·633 تفرعات·C++·Apache-2.0·7 مشاهداتkvrocks.apache.org↗

Incubator Kvrocks

Kvrocks is a disk-based NoSQL database and distributed key-value store that leverages the RocksDB storage engine to persist large datasets to physical disk. It is designed to be a Redis-compatible database, utilizing the standard Redis communication protocol to ensure interoperability with existing client libraries and tools.

The project distinguishes itself by combining a disk-persistent storage model with advanced retrieval capabilities, including vector search for k-nearest neighbor queries, full-text search indexing, and geospatial query execution. It supports distributed clustering with slot-based data distribution and topology management to enable horizontal scaling and high availability.

The system covers a wide array of data storage types, including JSON documents, streams, sorted sets, hash maps, and bitmaps. It provides comprehensive data management tools such as atomic transactions, log-based replication, and probabilistic data structures for cardinality estimation and membership checking. Additionally, it includes server-side scripting, pub/sub messaging, and detailed monitoring for server health and storage engine performance.

Features

  • Distributed Key-Value Stores - A scalable data system that manages data across multiple nodes using cluster topology and slot migration.
  • Disk-Based Key-Value Storage - Persists key-value data to disk using RocksDB to reduce memory costs while maintaining high-performance access.
  • Unbounded Key-Value Stores - Provides a disk-based key-value store using RocksDB to manage datasets that exceed physical memory.
  • LSM-Tree Storage Engines - Leverages a Log-Structured Merge-Tree storage engine to persist large datasets to physical disk.
  • Stream Append Operations - Records events with unique millisecond-sequence identifiers in an append-only data structure.
  • Cluster Request Redirections - Sends the correct node address to clients when a request hits a node not serving the target slot.
  • Cluster Topology Management - Configures node roles and slot assignments across a cluster using versioned updates to ensure consistency.
  • Embedded Storage Engines - Implements a high-performance storage layer based on the RocksDB embedded engine for disk-based persistence.
  • Disk-Based NoSQL Databases - Provides a disk-persistent NoSQL storage system for large key-value and JSON datasets.
  • Distributed Database Clusters - Organizes database nodes into a coordinated cluster for high availability and horizontal scaling.
  • Dynamic Slot Migrations - Moves data ownership between nodes in real time to enable scaling and load balancing.
  • Hash Field Management - Manages field-value pairs within hash structures with support for field-level expiration and numeric increments.
  • Hash Map Storage - Maps keys to field-value pairs by splitting entries to maintain performance as maps grow.
  • Incremental Data Synchronization - Synchronizes data from master nodes to replicas through incremental updates and full backup restoration.
  • JSON Document Storage - Saves semi-structured data using JSON or CBOR encoding for native document persistence.
  • JSON Document Manipulation - Provides logic for updating property values and modifying arrays within stored JSON documents.
  • Key-Value Pair Managers - Provides a primary storage mechanism for mapping keys to raw values with support for automatic expiration.
  • Ordered List Management - Maintains sequences of elements with support for blocking pops and atomic transfers.
  • Redis Cluster Deployments - Organizes multiple nodes into a cluster topology using a centralized controller to manage roles and slots.
  • Client-Compatible Topologies - Creates a cluster topology that works with standard cluster clients without requiring modifications.
  • Redis Compatible Stores - Implements the Redis protocol to ensure seamless compatibility with existing ecosystem clients and proxy tools.
  • String Value Assignments - Manages the assignment of string values to keys, including atomic updates and manipulation.
  • String Data Structures - Implements primitive string and binary storage with support for atomic increments and substring operations.
  • Capacity Scaling - Redistributes data slots between nodes to balance load or increase total storage capacity.
  • Primary-Replica Log Replication - Synchronizes state from master to replica nodes by streaming incremental change logs and snapshots.
  • Message Stream Consumer Groups - Appends and consumes entries in a log-like structure with support for parallel processing via consumer groups.
  • Hash Slot Sharding - Partitions the keyspace into fixed hash slots assigned to nodes for horizontal scaling.
  • Vector Databases and Search - Provides a specialized engine for storing and performing similarity searches on high-dimensional vector embeddings.
  • Backup and Recovery - Creates full and incremental copies of the dataset for disaster recovery and persistence.
  • Bitmap Storage - Implements fragmented storage for large sequences of bits to enable efficient arbitrary index writing.
  • Point-in-Time Database Snapshots - Generates point-in-time snapshots of the database to disk via complete or incremental copies.
  • Key Expiration Management - Handles key lifecycles using existence checks and time-to-live settings to control automatic eviction.
  • Atomic Transaction Execution - Groups multiple commands into atomic blocks to ensure they either execute completely or not at all.
  • Full Text Search - Creates and queries full-text search indexes to find documents matching specific text filters and keywords.
  • Full-Text Search Indexes - Creates and queries searchable full-text indexes to retrieve documents using complex text filters.
  • Geospatial Indexes - Implements geospatial indexing to calculate distances and find members within a specific radius.
  • Centroid-Based Approximations - Clusters data points into centroids to provide real-time approximations of quantiles for analytics.
  • Sorted Integer Sets - Stores and retrieves ranges of integers in a sorted collection for numerical range queries.
  • Binary Document Encodings - Saves structured JSON data using binary encoding to reduce disk usage and improve parsing speed.
  • Optimistic Locking - Provides atomic blocks that only execute if the underlying data has not changed since being read.
  • Probabilistic Data Structures - Uses sketches and filters to estimate set cardinality and membership with minimal memory overhead.
  • Probabilistic Membership Filters - Provides memory-efficient probabilistic filters to verify set membership with minimal false positives.
  • Real-Time Data Streaming - Manages chronological event logs and consumer groups for asynchronous data processing and messaging.
  • Complex Search Querying - Executes complex queries using search-compatible syntax or a subset of SQL SELECT statements for record retrieval.
  • Secondary Indexes - Provides secondary indexes on numeric and vector fields to enable complex queries over large datasets.
  • Server-Side Scripting - Executes scripts on the server to perform complex logic atomically and reduce network round-trips.
  • Sorted Sets - Maintains a set of unique integer members sorted in ascending order.
  • Compaction Management - Automatically merges and rewrites sorted runs in the background to reclaim space and maintain read performance.
  • Time Series Management - Supports the storage and querying of timestamped samples with built-in retention policies and range aggregation.
  • Unordered Unique Collection Management - Manages collections of unique elements and performs set-theoretic operations like intersections, unions, and differences.
  • Vector Search - Provides high-dimensional vector search capabilities including k-nearest neighbor and range queries.
  • Pub-Sub Messaging - Implements a publish-subscribe messaging system using named channels for asynchronous client communication.
  • Bitwise Logic Operations - Executes low-level bitwise logic operations including AND, OR, and XOR across stored keys.
  • Database Systems - Distributed NoSQL database compatible with Redis.
  • قواعد البيانات - Distributed key-value store compatible with Redis.

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الأسئلة الشائعة

ما هي وظيفة apache/incubator-kvrocks؟

Kvrocks is a disk-based NoSQL database and distributed key-value store that leverages the RocksDB storage engine to persist large datasets to physical disk. It is designed to be a Redis-compatible database, utilizing the standard Redis communication protocol to ensure interoperability with existing client libraries and tools.

ما هي الميزات الرئيسية لـ apache/incubator-kvrocks؟

الميزات الرئيسية لـ apache/incubator-kvrocks هي: Distributed Key-Value Stores, Disk-Based Key-Value Storage, Unbounded Key-Value Stores, LSM-Tree Storage Engines, Stream Append Operations, Cluster Request Redirections, Cluster Topology Management, Embedded Storage Engines.

ما هي البدائل مفتوحة المصدر لـ apache/incubator-kvrocks؟

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